LLM-Oriented Software Development Professors and Supervisors

Marianne Huchardمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Marianne Huchard is Full Professor of Computer Science at the University of Montpellier, Faculty of Sciences since 2004, serving as Director of LIRMM (Laboratory of Informatics, Robotics and Microelectronics at Montpellier) and head of its Computer Science Department. She also participates in the human resources committee of the MIPS scientific department. She earned her PhD in Computer Science in 1992 researching algorithmic aspects of multiple inheritance in object-oriented programming languages. Her primary research domains are Formal Concept Analysis (theoretical and applied, including Relational Concept Analysis) and Software Engineering (model-driven engineering, component-based development, and software product line migration), with recent work integrating Large Language Models for innovative solutions. Analysis of her 2024-2025 publications reveals a strong interdisciplinary trend: Relational Concept Analysis enhanced by LLMs is being applied to software engineering challenges like user-story generation, class model restructuring, and product line migration, demonstrating significant methodological innovation. Scientific awards: None documented in provided sources. She actively supervises doctoral research: Thomas Georges (defended January 2023): 'Agile Engineering of Software Product Lines for Agricultural Decision Support' Austin Waffo-Kouhoué (defended November 2024): 'Web Accessibility for People with Visual Impairments' Her research is supported by projects including RCAviz (funded by #DigitAg), FCA4J toolkit development, and Web Iris accessibility extension. As leader of the MAREL team (Models And Reuse Engineering, Languages) at LIRMM, she drives research at the formal methods/software engineering intersection and co-created Montpellier's Master's program in Software Engineering.

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Yiling Louمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Yiling Lou is an incoming Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign (starting Spring 2026), currently serving as a Pre-tenure Associate Professor at Fudan University. Previously a Postdoctoral Fellow at Purdue University under Prof. Lin Tan, Dr. Lou holds a Ph.D. and B.S. in Computer Science from Peking University supervised by Prof. Lu Zhang and Prof. Dan Hao. Research interests span Software Engineering synergized with Artificial Intelligence and Programming Languages , specifically focusing on LLM4Code, Agent&SE, Vulnerability Detection, and Software Testing/Debugging. Current projects include AgentIssue-Bench for agent system maintenance and INFERROI for enhancing static analysis with LLMs. Research trends show increasing integration of LLMs with traditional SE techniques, particularly in code generation (ClassEval, CodeGen4Libs), debugging (interactive runtime comparison), and vulnerability detection. Recent work emphasizes practical applications in agent systems and resource leak detection. ACM SIGSOFT Distinguished Paper Award (ESEC/FSE 2023) IEEE TCSE Distinguished Paper Award (ICSME 2021) Advises a large research group including 7 Ph.D. and 8 MS students at Fudan University, actively recruiting for UIUC starting Fall 2026. Leads the LLM4Code workshop series and serves on numerous program committees including ICSE, ASE, and FSE. Currently organizing research on Code Agents, Code LLMs, and AI&Security with strong industry relevance. Coordinates the Siebel School research group at UIUC focusing on the intersection of AI and Software Engineering, with particular emphasis on developing robust agent systems for code maintenance and security applications.

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Shing-Chi Cheungمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.

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Hui Liuمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Hui Liu is a Professor in the School of Computer Science and Technology at Beijing Institute of Technology, where he leads research in AI-based software development with a focus on LLM applications. His work spans software refactoring, quality improvement, and maintenance, funded by the National Natural Science Foundation of China and the National Key Research and Development Program of China. PhD from Peking University (2008) Former graduate student at Software Engineering Institute, Peking University Distinguished member of China Computer Federation Secretary-General of CCF Technical Committee on Software Engineering Professor Liu's research centers on LLM-based program generation, evaluation and testing of large language models, software refactoring techniques, and automatic construction of software engineering datasets. His work bridges artificial intelligence and software engineering, with particular emphasis on improving code quality through empirical studies and machine learning techniques. Current projects include code contamination detection, context-aware naming recommendations, and refactoring validation using LLMs. His research has evolved from traditional code smell detection to cutting-edge applications of large language models in software development. Liu's publication record shows a strong trend toward LLM applications in software engineering, with recent work focusing on code review generation, commit message generation, and refactoring validation using large language models. His research combines empirical methods with machine learning approaches, often analyzing large code corpora from open-source projects. The work spans both theoretical foundations and practical tool development, with several contributions merged into Eclipse as part of the open-source community. ACM Distinguished Paper Award (ESEC/FSE 2023) ACM Distinguished Paper Award (ICSE 2022) RE'2021 Best Research Paper Award IET Software Premium Award (2018) New Century Excellent Talents in University (2013) Beijing Higher Education Young Elite Teacher (2013) Professor Liu actively mentors PhD and Master's students, with recent graduates including Waseem Akram (awarded Outstanding Graduate) and several students publishing at top venues. His research is supported by major Chinese funding agencies, and he serves on program committees for leading software engineering conferences including ASE, ICSE, and FSE. He maintains strong industry connections through contributions to Eclipse and studies of open-source ecosystems like Rust. Liu leads a research group focused on AI for software engineering, with active projects on code generation, refactoring, and quality improvement. The group collaborates extensively with international researchers and contributes directly to open-source tools, particularly in the Eclipse ecosystem where multiple refactoring improvements have been merged.

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Klaus Weidenhauptمشاهده پروفایل

استاد

Hochschule Niederrhein University of Applied SciencesGermany

Prof. Klaus Weidenhaupt serves as a Professor and Computer Science Library Officer at the Niederrhein University of Applied Sciences within the Department of Electrical Engineering and Computer Science. He is a key member of the Gemeinschaftslabor Informatik (GLI), which provides shared computing facilities for computer science education and supports a wide range of software-oriented courses including Database Systems, Data Science, and Natural Language Processing. His academic interests are centered on data-driven technologies, with significant contributions in the areas of Information Retrieval , Web Mining , and Machine Learning . He teaches advanced courses such as Reinforcement Learning, Natural Language Processing, and IR and LLM-based web search, demonstrating expertise at the intersection of artificial intelligence and information systems. The GLI laboratory, where Prof. Weidenhaupt is based, operates multiple computer rooms equipped for practical instruction in software development, networking, and data processing. The laboratory also offers IT support services and manages virtual machine resources for academic projects, fostering a collaborative environment for students and faculty.

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